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GARCH Modelling of Cryptocurrencies

Citations

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Cited by:

  1. Saha, Kunal, 2018. "An investigation into the dependence structure of major cryptocurrencies," EconStor Preprints 181878, ZBW - Leibniz Information Centre for Economics.
  2. Imran Yousaf & Shoaib Ali, 2020. "Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-18, December.
  3. Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022. "On the volatility of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 62(C).
  4. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
  5. Lahmiri, Salim & Bekiros, Stelios, 2019. "Decomposing the persistence structure of Islamic and green crypto-currencies with nonlinear stepwise filtering," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 334-341.
  6. Haffar, Adlane & Le Fur, Éric, 2022. "Time-varying dependence of Bitcoin," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 211-220.
  7. Pınar Kaya Soylu & Mustafa Okur & Özgür Çatıkkaş & Z. Ayca Altintig, 2020. "Long Memory in the Volatility of Selected Cryptocurrencies: Bitcoin, Ethereum and Ripple," JRFM, MDPI, vol. 13(6), pages 1-21, May.
  8. Jules Clement Mba & Sutene Mwambi, 2020. "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 199-214, June.
  9. Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2020. "Do Bitcoin and other cryptocurrencies jump together?," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 396-409.
  10. Charles Shaw, 2018. "Conditional heteroskedasticity in crypto-asset returns," Papers 1804.07978, arXiv.org, revised Dec 2018.
  11. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).
  12. Yi, Yongsheng & He, Mengxi & Zhang, Yaojie, 2022. "Out-of-sample prediction of Bitcoin realized volatility: Do other cryptocurrencies help?," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  13. Ke, Rui & Yang, Luyao & Tan, Changchun, 2022. "Forecasting tail risk for Bitcoin: A dynamic peak over threshold approach," Finance Research Letters, Elsevier, vol. 49(C).
  14. Corbet, Shaen & Cumming, Douglas J. & Lucey, Brian M. & Peat, Maurice & Vigne, Samuel A., 2020. "The destabilising effects of cryptocurrency cybercriminality," Economics Letters, Elsevier, vol. 191(C).
  15. Iqbal, Najaf & Fareed, Zeeshan & Wan, Guangcai & Shahzad, Farrukh, 2021. "Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 73(C).
  16. Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
  17. Omane-Adjepong, Maurice & Alagidede, Paul & Akosah, Nana Kwame, 2019. "Wavelet time-scale persistence analysis of cryptocurrency market returns and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 105-120.
  18. Haffar, Adlane & Le Fur, Eric, 2021. "Structural vector error correction modelling of Bitcoin price," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 170-178.
  19. Shrestha, Prabal & Arslan-Ayaydin, Özgür & Thewissen, James & Torsin, Wouter, 2021. "Institutions, regulations and initial coin offerings: An international perspective," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 102-120.
  20. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
  21. Yhlas Sovbetov, 2018. "Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 1-27.
  22. Parthajit Kayal & G. Balasubramanian, 2021. "Excess Volatility in Bitcoin: Extreme Value Volatility Estimation," IIM Kozhikode Society & Management Review, , vol. 10(2), pages 222-231, July.
  23. Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
  24. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
  25. Eduard Silantyev, 2019. "Order flow analysis of cryptocurrency markets," Digital Finance, Springer, vol. 1(1), pages 191-218, November.
  26. Kazeem Abimbola Sanusi & Zandri Dickason-Koekemoer, 2022. "Cryptocurrency Returns, Cybercrime and Stock Market Volatility: GAS and Regime Switching Approaches," International Journal of Economics and Financial Issues, Econjournals, vol. 12(6), pages 52-64, November.
  27. Sercan Demiralay & Selçuk Bayracı, 2021. "Should stock investors include cryptocurrencies in their portfolios after all? Evidence from a conditional diversification benefits measure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6188-6204, October.
  28. Kraaijeveld, Olivier & De Smedt, Johannes, 2020. "The predictive power of public Twitter sentiment for forecasting cryptocurrency prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
  29. Leandro Maciel, 2021. "Cryptocurrencies value‐at‐risk and expected shortfall: Do regime‐switching volatility models improve forecasting?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4840-4855, July.
  30. Salisu, Afees A. & Ogbonna, Ahamuefula E., 2022. "The return volatility of cryptocurrencies during the COVID-19 pandemic: Assessing the news effect," Global Finance Journal, Elsevier, vol. 54(C).
  31. Wüstenfeld, Jan & Geldner, Teo, 2022. "Economic uncertainty and national bitcoin trading activity," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
  32. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
  33. Vahidin Jeleskovic & Mirko Meloni & Zahid Irshad Younas, 2020. "Cryptocurrencies: A Copula Based Approach for Asymmetric Risk Marginal Allocations," MAGKS Papers on Economics 202034, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  34. Yuan Hu & Svetlozar T. Rachev & Frank J. Fabozzi, 2019. "Modelling Crypto Asset Price Dynamics, Optimal Crypto Portfolio, and Crypto Option Valuation," Papers 1908.05419, arXiv.org.
  35. Viviane Naimy & Omar Haddad & Gema Fernández-Avilés & Rim El Khoury, 2021. "The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-17, January.
  36. Apopo, Natalay & Phiri, Andrew, 2019. "On the (in)efficiency of cryptocurrencies: Have they taken daily or weekly random walks?," MPRA Paper 94712, University Library of Munich, Germany.
  37. Manavi, Seyed Alireza & Jafari, Gholamreza & Rouhani, Shahin & Ausloos, Marcel, 2020. "Demythifying the belief in cryptocurrencies decentralized aspects. A study of cryptocurrencies time cross-correlations with common currencies, commodities and financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
  38. Zexuan Yin & Paolo Barucca, 2022. "Neural Generalised AutoRegressive Conditional Heteroskedasticity," Papers 2202.11285, arXiv.org.
  39. Marian Gidea & Daniel Goldsmith & Yuri Katz & Pablo Roldan & Yonah Shmalo, 2018. "Topological recognition of critical transitions in time series of cryptocurrencies," Papers 1809.00695, arXiv.org.
  40. Kristjanpoller, Werner & Bouri, Elie & Takaishi, Tetsuya, 2020. "Cryptocurrencies and equity funds: Evidence from an asymmetric multifractal analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
  41. Deniz Erer, 2023. "The Impact of News Related Covid-19 on Exchange Rate Volatility:A New Evidence From Generalized Autoregressive Score Model," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(38), pages 105-126, June.
  42. Samuel Asante Gyamerah, 2019. "Estimating the volatility of Bitcoin using GARCH models," Papers 1909.04903, arXiv.org, revised Oct 2019.
  43. Yokoyama, Kazuki, 2023. "Whispers of Chaos: Intervention on the Mexican Dollar Quotes in Japan, 1869-1885," MPRA Paper 118586, University Library of Munich, Germany.
  44. Shan Wu, 2021. "Co-movement and return spillover: evidence from Bitcoin and traditional assets," SN Business & Economics, Springer, vol. 1(10), pages 1-16, October.
  45. Katsiampa, Paraskevi, 2019. "An empirical investigation of volatility dynamics in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 50(C), pages 322-335.
  46. Dean Fantazzini & Stephan Zimin, 2020. "A multivariate approach for the simultaneous modelling of market risk and credit risk for cryptocurrencies," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 19-69, March.
  47. James, Nick & Menzies, Max & Chan, Jennifer, 2021. "Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
  48. Naeem, Muhammad & Bouri, Elie & Boako, Gideon & Roubaud, David, 2020. "Tail dependence in the return-volume of leading cryptocurrencies," Finance Research Letters, Elsevier, vol. 36(C).
  49. Klein, Tony & Pham Thu, Hien & Walther, Thomas, 2018. "Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 105-116.
  50. Shaw, Charles, 2018. "Conditional heteroskedasticity in crypto-asset returns," MPRA Paper 90437, University Library of Munich, Germany.
  51. Hayet Ben Haj Hamida & Francesco Scalera, 2019. "Threshold Mean Reversion and Regime Changes of Cryptocurrencies using SETAR-MSGARCH Models," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 9(3), pages 221-229, July.
  52. Köchling, Gerrit & Schmidtke, Philipp & Posch, Peter N., 2020. "Volatility forecasting accuracy for Bitcoin," Economics Letters, Elsevier, vol. 191(C).
  53. Amélie Charles & Olivier Darné, 2019. "Volatility estimation for cryptocurrencies: Further evidence with jumps and structural breaks," Economics Bulletin, AccessEcon, vol. 39(2), pages 954-968.
  54. Bergsli, Lykke Øverland & Lind, Andrea Falk & Molnár, Peter & Polasik, Michał, 2022. "Forecasting volatility of Bitcoin," Research in International Business and Finance, Elsevier, vol. 59(C).
  55. Matthias Schnaubelt & Jonas Rende & Christopher Krauss, 2019. "Testing Stylized Facts of Bitcoin Limit Order Books," JRFM, MDPI, vol. 12(1), pages 1-30, February.
  56. Thomas Walther & Tony Klein, 2018. "Exogenous Drivers of Cryptocurrency Volatility - A Mixed Data Sampling Approach To Forecasting," Working Papers on Finance 1815, University of St. Gallen, School of Finance.
  57. Caporale, Guglielmo Maria & Zekokh, Timur, 2019. "Modelling volatility of cryptocurrencies using Markov-Switching GARCH models," Research in International Business and Finance, Elsevier, vol. 48(C), pages 143-155.
  58. Anupam Dutta & Elie Bouri, 2022. "Outliers and Time-Varying Jumps in the Cryptocurrency Markets," JRFM, MDPI, vol. 15(3), pages 1-7, March.
  59. Panayiotis Theodossiou & Polina Ellina & Christos S. Savva, 2022. "Stochastic properties and pricing of bitcoin using a GJR-GARCH model with conditional skewness and kurtosis components," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 695-716, August.
  60. Cristina Chinazzo & Vahidin Jeleskovic, 2024. "Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches," Papers 2401.02049, arXiv.org.
  61. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
  62. Roy Cerqueti & Massimiliano Giacalone & Raffaele Mattera, 2020. "Skewed non-Gaussian GARCH models for cryptocurrencies volatility modelling," Papers 2004.11674, arXiv.org.
  63. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
  64. López-Martín, Carmen & Arguedas-Sanz, Raquel & Muela, Sonia Benito, 2022. "A cryptocurrency empirical study focused on evaluating their distribution functions," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 387-407.
  65. Pierre J. Venter & Eben Maré, 2020. "GARCH Generated Volatility Indices of Bitcoin and CRIX," JRFM, MDPI, vol. 13(6), pages 1-15, June.
  66. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
  67. Brini, Alessio & Lenz, Jimmie, 2022. "Assessing the resiliency of investors against cryptocurrency market crashes through the leverage effect," Economics Letters, Elsevier, vol. 220(C).
  68. Francisco Javier García-Corral & José Antonio Cordero-García & Jaime de Pablo-Valenciano & Juan Uribe-Toril, 2022. "A bibliometric review of cryptocurrencies: how have they grown?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-31, December.
  69. Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
  70. Gkillas, Konstantinos & Katsiampa, Paraskevi, 2018. "An application of extreme value theory to cryptocurrencies," Economics Letters, Elsevier, vol. 164(C), pages 109-111.
  71. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "The volatility surprise of leading cryptocurrencies: Transitory and permanent linkages," Finance Research Letters, Elsevier, vol. 33(C).
  72. Elie Bouri & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting Realized Volatility of Bitcoin: The Role of the Trade War," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 29-53, January.
  73. Vahidin Jeleskovic & Claudio Latini & Zahid I. Younas & Mamdouh A. S. Al-Faryan, 2023. "Optimization of portfolios with cryptocurrencies: Markowitz and GARCH-Copula model approach," Papers 2401.00507, arXiv.org.
  74. Mawuli Segnon & Stelios Bekiros, 2020. "Forecasting volatility in bitcoin market," Annals of Finance, Springer, vol. 16(3), pages 435-462, September.
  75. Lepomäki, Laura & Kanniainen, Juho & Hansen, Henri, 2021. "Retaliation in Bitcoin networks," Economics Letters, Elsevier, vol. 203(C).
  76. Gregor Dorfleitner & Carina Lung, 2018. "Cryptocurrencies from the perspective of euro investors: a re-examination of diversification benefits and a new day-of-the-week effect," Journal of Asset Management, Palgrave Macmillan, vol. 19(7), pages 472-494, December.
  77. George Tzagkarakis & Frantz Maurer, 2023. "Horizon-Adaptive Extreme Risk Quantification for Cryptocurrency Assets," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1251-1286, October.
  78. Chappell, Daniel, 2018. "Regime heteroskedasticity in Bitcoin: A comparison of Markov switching models," MPRA Paper 90682, University Library of Munich, Germany.
  79. Toshiyuki Yam awake & Joseph Sheely & Roberto Serrano & Jiro Hodoshima, 2022. "Comparative Performance of Cryptocurrencies through the Aumann and Serrano Economic Index of Riskiness," Working Papers 2022-007, Brown University, Department of Economics.
  80. Rama K. Malladi & Prakash L. Dheeriya, 2021. "Time series analysis of Cryptocurrency returns and volatilities," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(1), pages 75-94, January.
  81. Jules Clement Mba & Edson Pindza & Ur Koumba, 2018. "A differential evolution copula-based approach for a multi-period cryptocurrency portfolio optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(4), pages 399-418, November.
  82. Inés Jiménez & Andrés Mora-Valencia & Javier Perote, 2022. "Dynamic selection of Gram–Charlier expansions with risk targets: an application to cryptocurrencies," Risk Management, Palgrave Macmillan, vol. 24(1), pages 81-99, March.
  83. Zexuan Yin & Paolo Barucca, 2022. "Variational Heteroscedastic Volatility Model," Papers 2204.05806, arXiv.org.
  84. Maurice Omane‐Adjepong & Imhotep Paul Alagidede, 2021. "Modelling Asymmetry and Leverage in Cryptocurrencies and Emerging Financial Markets," Economic Papers, The Economic Society of Australia, vol. 40(2), pages 152-166, June.
  85. Tak Kuen Siu, 2023. "Bayesian nonlinear expectation for time series modelling and its application to Bitcoin," Empirical Economics, Springer, vol. 64(1), pages 505-537, January.
  86. Jiang, Kunliang & Zeng, Linhui & Song, Jiashan & Liu, Yimeng, 2022. "Forecasting Value-at-Risk of cryptocurrencies using the time-varying mixture-accelerating generalized autoregressive score model," Research in International Business and Finance, Elsevier, vol. 61(C).
  87. Yaojie Zhang & Mengxi He & Danyan Wen & Yudong Wang, 2022. "Forecasting Bitcoin volatility: A new insight from the threshold regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 633-652, April.
  88. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
  89. Gidea, Marian & Goldsmith, Daniel & Katz, Yuri & Roldan, Pablo & Shmalo, Yonah, 2020. "Topological recognition of critical transitions in time series of cryptocurrencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
  90. Thomas Dimpfl & Stefania Odelli, 2020. "Bitcoin Price Risk—A Durations Perspective," JRFM, MDPI, vol. 13(7), pages 1-18, July.
  91. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
  92. Beatriz Mota Aragón & José Antonio Núñez Mora, 2019. "Estimación de la distribución multivariada de los rendimientos de los tipos de cambio contra el dólar de las criptomonedas Bitcoin, Ripple y Ether," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 14(3), pages 447-457, Julio - S.
  93. C. Y. Tan & Y. B. Koh & K. H. Ng & K. H. Ng, 2019. "Structural Change Analysis of Active Cryptocurrency Market," Papers 1909.10679, arXiv.org.
  94. Ahmed Ibrahim & Rasha Kashef & Menglu Li & Esteban Valencia & Eric Huang, 2020. "Bitcoin Network Mechanics: Forecasting the BTC Closing Price Using Vector Auto-Regression Models Based on Endogenous and Exogenous Feature Variables," JRFM, MDPI, vol. 13(9), pages 1-21, August.
  95. Konstantin Gorgen & Jonas Meirer & Melanie Schienle, 2022. "Predicting Value at Risk for Cryptocurrencies With Generalized Random Forests," Papers 2203.08224, arXiv.org, revised Jun 2022.
  96. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
  97. D’Amato, Valeria & Levantesi, Susanna & Piscopo, Gabriella, 2022. "Deep learning in predicting cryptocurrency volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
  98. Feng Ma & Chao Liang & Yuanhui Ma & M.I.M. Wahab, 2020. "Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1277-1290, December.
  99. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
  100. Walther, Thomas & Klein, Tony & Bouri, Elie, 2018. "Exogenous Drivers of Bitcoin and Cryptocurrency Volatility – A Mixed Data Sampling Approach to Forecasting," QBS Working Paper Series 2018/02, Queen's University Belfast, Queen's Business School.
  101. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
  102. Farman Ullah Khan & Faridoon Khan & Parvez Ahmed Shaikh, 2023. "Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
  103. Wang, Yizhi & Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa, 2022. "The Effects of Central Bank Digital Currencies News on Financial Markets," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
  104. Bojaj, Martin M. & Muhadinovic, Milica & Bracanovic, Andrej & Mihailovic, Andrej & Radulovic, Mladen & Jolicic, Ivan & Milosevic, Igor & Milacic, Veselin, 2022. "Forecasting macroeconomic effects of stablecoin adoption: A Bayesian approach," Economic Modelling, Elsevier, vol. 109(C).
  105. Qureshi, Saba & Aftab, Muhammad & Bouri, Elie & Saeed, Tareq, 2020. "Dynamic interdependence of cryptocurrency markets: An analysis across time and frequency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
  106. Chika Anastesia Anisiuba & Obiamaka P. Egbo & Felix C. Alio & Chuka Ifediora & Ebele C. Igwemeka & C. O. Odidi & Hillary Chijindu Ezeaku, 2021. "Analysis of Cryptocurrency Dynamics in the Emerging Market Economies: Does Reinforcement or Substitution Effect Prevail?," SAGE Open, , vol. 11(1), pages 21582440211, March.
  107. Mamoona Zahid & Farhat Iqbal & Dimitrios Koutmos, 2022. "Forecasting Bitcoin Volatility Using Hybrid GARCH Models with Machine Learning," Risks, MDPI, vol. 10(12), pages 1-18, December.
  108. Akcora, Cuneyt Gurcan & Dixon, Matthew F. & Gel, Yulia R. & Kantarcioglu, Murat, 2018. "Bitcoin risk modeling with blockchain graphs," Economics Letters, Elsevier, vol. 173(C), pages 138-142.
  109. Branimir Cvitko Cicvarić, 2020. "Volatility of Cryptocurrencies," Notitia - journal for economic, business and social issues, Notitia Ltd., vol. 1(6), pages 13-23, December.
  110. Micu Raluca & Dumitrescu Dalina, 2022. "Study regarding the volatility of main cryptocurrencies," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 179-187, August.
  111. Cuneyt Akcora & Matthew Dixon & Yulia Gel & Murat Kantarcioglu, 2018. "Bitcoin Risk Modeling with Blockchain Graphs," Papers 1805.04698, arXiv.org.
  112. Matthew F. Dixon & Cuneyt Gurcan Akcora & Yulia R. Gel & Murat Kantarcioglu, 2019. "Blockchain analytics for intraday financial risk modeling," Digital Finance, Springer, vol. 1(1), pages 67-89, November.
  113. Angerer, Martin & Hoffmann, Christian Hugo & Neitzert, Florian & Kraus, Sascha, 2021. "Objective and subjective risks of investing into cryptocurrencies," Finance Research Letters, Elsevier, vol. 40(C).
  114. Owusu Junior, Peterson & Tiwari, Aviral Kumar & Tweneboah, George & Asafo-Adjei, Emmanuel, 2022. "GAS and GARCH based value-at-risk modeling of precious metals," Resources Policy, Elsevier, vol. 75(C).
  115. Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
  116. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
  117. Huthaifa Alqaralleh & Alaa Adden Abuhommous & Ahmad Alsaraireh, 2020. "Modelling and Forecasting the Volatility of Cryptocurrencies: A Comparison of Nonlinear GARCH-Type Models," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(4), pages 346-356, July.
  118. Stephen Chan & Saralees Nadarajah, 2020. "Extreme Values and Financial Risk," JRFM, MDPI, vol. 13(2), pages 1-3, February.
  119. Qiu, Yue & Wang, Yifan & Xie, Tian, 2021. "Forecasting Bitcoin realized volatility by measuring the spillover effect among cryptocurrencies," Economics Letters, Elsevier, vol. 208(C).
  120. Klein, Tony & Hien, Pham Thu & Walther, Thomas, 2018. "Bitcoin Is Not the New Gold: A Comparison of Volatility, Correlation, and Portfolio Performance," QBS Working Paper Series 2018/01, Queen's University Belfast, Queen's Business School.
  121. Sabah, Nasim, 2020. "Cryptocurrency accepting venues, investor attention, and volatility," Finance Research Letters, Elsevier, vol. 36(C).
  122. Jennifer Castle & Takamitsu Kurita, 2022. "Structural relationships between cryptocurrency prices and monetary policy indicators," Economics Series Working Papers 972, University of Oxford, Department of Economics.
  123. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.
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